Triple

T32025566

Position	Surface form	Disambiguated ID	Type / Status
Subject	Diwan of Mysore	`E817807`	entity
Predicate	officeHolderTitleInKannada	`P198735`	FINISHED
Object	Dewan Dewan was the title given to the chief minister or prime administrative officer in several Indian princely states, including Mysore, during the pre-independence era.	`E1988534`	NE FINISHED

How this triple was built (3 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini

Instruction

Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).

Input

Phrase: Dewan | Statement: [Diwan of Mysore, officeHolderTitleInKannada, Dewan]

NEDg Description generation gpt-5.1

Instruction

Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"

Input

Entity: Dewan
Triple: [Diwan of Mysore, officeHolderTitleInKannada, Dewan]

Generated description

Dewan was the title given to the chief minister or prime administrative officer in several Indian princely states, including Mysore, during the pre-independence era.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: officeHolderTitleInKannada
Context triple: [Diwan of Mysore, officeHolderTitleInKannada, Dewan]

A. officeHolderTitle
Indicates the official position or title held by a person in an office or role.
B. officeHolderTitleInKorean
Indicates the official title or designation of an office holder as expressed in the Korean language.
C. officeHolderTitleInJapanese
Indicates the official title or designation of an office holder as expressed in the Japanese language.
D. typicalOfficeHolderTitle
Indicates the standard or commonly used title typically held by the office holder of a given position or role.
E. residenceOfOfficeHolderTitle
Indicates the place where a person holding a particular official title resides while in that role.
F. None of above. chosen

Provenance (7 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step	Stage	Batch ID	Status	When
creating	Elicitation	`batch_69f348fb04e4819081f4eab040ed7959`	completed	April 30, 2026, 12:20 p.m.
NER	Named-entity recognition	`batch_69ff0214d7348190904688376df99bce`	completed	May 9, 2026, 9:44 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a2ed4edc49c8190954488a518693cf4`	completed	June 14, 2026, 4:21 p.m.
NEDg	Description generation	`batch_6a2ed627b97481908e0d618ba90fb9ec`	completed	June 14, 2026, 4:26 p.m.
NED2	Entity disambiguation (via description)	`batch_6a2ed6f938548190b1151d9ee583f82b`	completed	June 14, 2026, 4:29 p.m.
PD	Predicate disambiguation	`batch_69feffd62fec8190a855922c8b3c57cf`	completed	May 9, 2026, 9:35 a.m.
PDg	Predicate description generation	`batch_69ff02141dbc8190b00bcea2aa734b3a`	completed	May 9, 2026, 9:44 a.m.

Created at: May 1, 2026, 12:17 a.m.